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Cross Sectional Study Strengths And Weaknesses

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Cross-sectional and the longitudinal studies are studies in which researcher do not control the environment in order to record information. Cross-sectional study contrast different population at a snapshot or solitary point in time.This is like a drawing that fits perfectly in the frame. The advantage of this kind of study is that it allows researchers to study different variables at the same time. Cross-sectional studies occasionally supply precise information about cause-and-effect relationships. This is because the study only offer a snapshot at a solitary point in time. However, longitudinal study, researchers conduct a lot observations of the identical subject over an interval of time occasionally lasting many years. A benefit of longitudinal study is that the researcher is not able to uncover maturation or make or become a …show more content…

longitudinal studies a person want to study a sequence of event then they would go with this one. Cross-sectional studies would be used in general because it done more quickly than longitudinal studies,but the most reliable would be longitudinal studies because of its broad study with sequence of events.Longitudinal studies strengths are extending time which is a benefit. Also, this study separates real trends from chance occurrence. Another strength is Useful for charting growth and development..Some weakness of Longitudinal studies is it too time consuming. Also this study cost to much.Another weakness is Control effects repeated interviewing of the same sample influences their behaviour. Some strengths of cross-sectional study is cheap to administer, and it is quick to conduct. Another, strengths of cross-sectional study is Charts aggregated pattern. Some weakness of cross-sectional study is do not permit analysis of causal relationships. Also, Unable to chart individual variations in development or changes, and their significance. Another, weakness of cross-sectional study is Unable to chart changing social processes over

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